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What is DeepSeek-V3.1-Terminus?

DeepSeek has introduced DeepSeek-V3.1-Terminus, an enhanced version of the V3.1 architecture that incorporates user feedback to improve output reliability, uniformity, and overall performance of the agent. This upgrade notably reduces the frequency of mixed Chinese and English text as well as unintended anomalies, resulting in a more polished and cohesive language generation experience. Furthermore, the update overhauls both the code agent and search agent subsystems, yielding better and more consistent performance across a range of benchmarks. DeepSeek-V3.1-Terminus is released as an open-source model, with its weights made available on Hugging Face, thereby facilitating easier access for the community to utilize its functionalities. The model's architecture stays consistent with that of DeepSeek-V3, ensuring compatibility with existing deployment strategies, while updated inference demonstrations are provided for users to investigate its capabilities. Impressively, the model functions at a massive scale of 685 billion parameters and accommodates various tensor formats, such as FP8, BF16, and F32, which enhances its adaptability in diverse environments. This versatility empowers developers to select the most appropriate format tailored to their specific requirements and resource limitations, thereby optimizing performance in their respective applications.

What is DeepInfer?

DeepInfer is an open-source framework tailored for running DeepSeek language models on Linux systems equipped with compatible NVIDIA or Huawei Ascend accelerators. It boasts a range of features intended to streamline offline inference and enhance model performance, such as optimized kernels, distributed parallelism, asynchronous batch scheduling, speculative decoding, and the creation of structured outputs in formats including JSON Schema, regular expressions, and EBNF. The documentation for the project includes support details for DeepSeek-V4.1-Flash, along with thorough instructions for building, configuring, and utilizing various examples and evaluation tools. Targeted at developers and infrastructure teams, it aids in the development or evaluation of self-managed inference deployments. Furthermore, the repository emphasizes that for production environments, additional components like KV-cache, prefill/decode disaggregation, and load-balancing mechanisms may be necessary, making users conscious of possible extra requirements as they implement the framework. In summary, DeepInfer not only optimizes the deployment of language models across diverse applications but also caters to both essential and sophisticated operational needs, making it a versatile tool for developers. This framework ultimately encourages innovation in language processing and model deployment strategies.

Media

Media

Integrations Supported

Hugging Face

Integrations Supported

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad

Supported Platforms

On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

api-docs.deepseek.com/news/news250922

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

github.com/deepseek-ai/DeepInfer

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Categories and Features

AI Inference

Not specified

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